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Download (1393Kb) University of Warwick institutional repository: http://go.warwick.ac.uk/wrap A Thesis Submitted for the Degree of PhD at the University of Warwick http://go.warwick.ac.uk/wrap/55431 This thesis is made available online and is protected by original copyright. Please scroll down to view the document itself. Please refer to the repository record for this item for information to help you to cite it. Our policy information is available from the repository home page. A Multidimensional Analysis of Post-Acquisition Performance: The Case of Research and Development in the Pharmaceutical Sector Rupert Julian Booth Thesis submitted for the degree of Doctor of Philosophy in Business & Management Studies University of Warwick, Coventry Warwick Business School September 2011 Contents Acknowledgments xii Declaration xiii Abstract xiv Glossary xv 1 Introduction 1 1.1 Research Aim 1 1.2 Choice of Sector and Need for Research 3 1.3 Research Approach 4 1.4 Research Hypotheses 5 1.5 Technical Challenges and Contributions to Knowledge 7 1.5.1 Measurement of Intangibles 7 1.5.2 Longitudinal Nature of R&D Pipeline 7 1.5.3 Variety of Outputs 8 1.5.4 Types of Contributions to Knowledge 8 2 Overview of Pharmaceutical Sector 10 2.1 Introduction 10 2.2 R&D Processes 10 2.3 Market Structure and Acquisition Activity 13 2.4 Key Metrics 14 ii 3 Literature Review 16 3.1 Introduction 16 3.2 PAP 16 3.2.1 History 16 3.2.2 Meta-Analyses 17 3.2.3 Summary of Main Approaches 24 3.2.4 Motive and Synergy 26 3.2.5 Diversification Literature 27 3.3 RBV 29 3.3.1 Early Definition of the RBV 29 3.3.2 Qualification of Resources 30 3.3.3 Dynamic RBV 31 3.3.4 Critiques of the RBV 31 3.3.5 Recent Retrospective on the RBV 33 3.3.6 Summary of Key Issues for Performance Measurement 34 3.4 PMFs 35 3.4.1 Theoretical Benefit of Additional Information 35 3.4.2 Benefits of PMFs 36 3.4.3 The Balanced Scorecard and its Evolution 37 3.4.4 Choice of Measures 40 3.4.5 External Evaluation of Intellectual Capital 41 3.5 Use of the RBV to Measure Performance in Pharmaceuticals 44 3.6 Relevant DEA Literature 48 3.7 Synthesis 50 4 Design of PMF 52 4.1 Introduction 52 iii 4.2 PMF Design Principles 52 4.3 Availability of Information 56 4.3.1 Practicality 56 4.3.2 Scope and Structure 56 4.3.3 Resources and Barriers 57 4.3.4 Processes and Positions 59 4.3.5 Efficiency 60 4.4 Application of Design Principles to the Pharmaceutical Sector 61 4.4.1 Demonstration of Use 61 4.4.2 Scope and Structure 61 4.4.3 Resources and Barriers 63 4.4.4 Processes and Positions 64 4.4.5 Efficiency 65 4.5 Proposed Pharmaceutical PMF 66 4.5.1 Outcome of Design Principles 66 4.5.2 Use of Negative Indicators 68 4.5.3 Choice of Financial Measures 68 4.6 Focus on R&D and Adaptation to DEA 69 4.7 Conclusion 71 5 Research Methodology 72 5.1 Introduction 72 5.2 Efficiency and Productivity Analysis Approaches 72 5.3 Summary of DEA Model 74 5.3.1 Orientation of Model 74 5.3.2 Inputs and Outputs 75 iv 5.4 Longitudinal Dimension 76 5.5 Definition of Notation 77 5.5.1 MCT 77 5.5.2 Normalisation Factor 78 5.5.3 Algebraic Notation for Efficiency Analysis 79 5.5.4 Form of DEA Equations 81 5.5.5 Algebraic Notation for Examination of Returns to Scale 82 5.5.6 Algebraic Notation for Classification of Acquisition History 83 5.5.7 Algebraic Notation for Statistical Testing 84 5.6 DEA 85 5.7 CCR Model 86 5.8 BCC Model 87 5.9 Output Weight Restrictions 88 5.10 Input Weight Restrictions 89 5.11 Returns to Scale 89 5.12 Design and Population of Acquisition Typology 90 5.12.1 Identification of Acquisitions 90 5.12.2 Classification of Acquisitions 92 5.12.3 Identification of Cross-border and Cross-sector Acquisitions 92 5.12.4 Linkage to Major Pharmaceutical Companies 94 5.13 Analysis of M&A History 95 5.14 Statistical Test Approach 96 5.15 Incomplete Data 99 6 Data and Descriptive Statistics 100 6.1 Introduction 100 v 6.2 Available Input Data for the DEA Models 101 6.3 Available Output Data for the DEA Models 101 6.4 Comparing CRS and VRS Efficiency Scores 102 6.5 DEA Model Results: Comparing Input Assumptions 102 6.6 Financial Efficiency Data 103 6.7 Acquisition and NDV Data 103 6.8 Association of M&A and Technical Efficiency 103 6.9 Association of M&A and Financial Efficiency 104 6.10 Descriptive Statistics of the DEA Model Outputs 104 6.11 Descriptive Statistics of the R&D Process 106 6.12 Descriptive Statistics of M&A 109 6.13 Summary 112 7HypothesisTesting 113 7.1 Scope of Hypothesis Testing 113 7.1.1 Classical Hypothesis Testing Model 113 7.1.2 Set 1, Hypothesis 1: Returns to Scale 115 7.1.3 Set 2, Hypotheses 2, 3 & 4: Firm Acquisition History and Technical Efficiency 116 7.1.4 Set 3, Hypotheses 5, 6 & 7: Deal History and Financial Efficiency 117 7.1.5 Set 4, Hypotheses 8, 9 & 10: Acquisition History and Sectoral Efficiency 118 7.1.6 Set 5, Hypotheses 11, 12, 13 & 14: Acquisition History and Sales over Assets 120 7.2 Returns to Scale (H1) 121 7.3 M&A and Technical Efficiency (H2, H3, H4) 122 7.3.1 Hypothesis 2 122 7.3.2 Hypothesis 3 123 vi 7.3.3 Hypothesis 4 124 7.3.4 Summary of the Set 125 7.4 M&A and Financial Efficiency (H5, H6, H7) 126 7.4.1 Hypothesis 5 126 7.4.2 Hypothesis 6 127 7.4.3 Hypothesis 7 128 7.4.4 Summary of the Set 129 7.5 Sector Effects and Technical Efficiency (H8, H9, H10) 130 7.5.1 Hypothesis 8 130 7.5.2 Hypothesis 9 130 7.5.3 Hypothesis 10 131 7.5.4 Summary of the Set 132 7.6 M&A and Financial Metrics (H11, H12, H13, H14) 132 7.6.1 Hypothesis 11 132 7.6.2 Hypothesis 12 133 7.6.3 Hypotheses 13 & 14 133 7.6.4 Summary of the Set 135 7.7 Summary of Findings 135 7.7.1 Collation of Findings 135 7.7.2 Check for Consistency 136 8 Discussion of Results 139 8.1 Range of Findings 139 8.2 Returns to Scale of R&D 140 8.3 The Association of Technical Efficiency with M&A History 141 vii 8.4 The Association of Financial Efficiency with M&A History 142 8.5 The Sectoral Consequences of M&A 143 8.6 Relationship between SOA and M&A 144 8.7 Synthesis of Findings 145 9 Contributions 149 9.1 Overview 149 9.2 Contributions to the Acquisition Literature 150 9.2.1 Reduction of Uncertainty 151 9.2.2 Differences in Measured Performance 151 9.2.3 Diversification 153 9.3 Contributions to the Performance Literature 153 9.4 Contributions to the DEA Literature 154 9.5 Empirical Contributions 154 9.5.1 Returns to Scale 154 9.5.2 Power Laws in M&A 155 9.5.3 Financial Metrics in M&A 156 9.6 Directions of Future Research 157 10 References 158 viii A. R&D Data 182 A.1 Introduction 182 A.2 Historical R&D Data 182 A.3 Historical Sales Data 185 A.4 Current R&D & Composite R&D Data 188 A.5 Conclusion 193 B. Staff Data 194 B.1 Introduction 194 B.2 Staff Data 194 C. Power Laws 198 C.1 Introduction 198 C.2 Definition of a Power Law 198 C.3 Alternative Distributions 199 C.4 Relevance to this Thesis 200 D. DEA Model Data 201 E. AcquisitionData 242 E.1 Introduction 242 E.2 Search Criteria 242 E.3 Annual Analysis 244 E.4 Detailed Merger Data 246 ix List of Tables 3.1 Choice of Measures in Acquisition Meta-Analysis 1983–2006 ................. 19 3.2 Contributions of the Major RBV Authors to Performance Measurement.... 34 3.3 Summary of Balanced Scorecard Concepts .............................................39 3.4 Parameters and Metrics Cited in DeCarolis & Deeds (1999) .................... 45 3.5 Outcomes of Hypotheses Testing in DeCarolis & Deeds (1999) .............. 46 3.6 Parameters and Metrics in DeCarolis (2003) ...........................................47 3.7 Outcomes of Hypotheses from DeCarolis (2003) .....................................48 4.1 Design Principles ..................................................................................... 53 4.2 Proposed Pharmaceutical PMF ............................................................... 66 4.3 Scorecard for Pharmaceutical Company .................................................. 67 5.1 Time and Costs of R&D Development .....................................................76 5.2 Algebraic Notation for DEA Models .......................................................... 80 5.3 Algebraic Notation for Examining Returns to Scale .................................. 82 5.4 Algebraic Notation for Classification of Acquisition History ....................... 83 5.5 Algebraic Notation for Hypothesis Testing ...............................................85 5.6 Selection Criteria ..................................................................................... 91 5.7 Key Terms for Acquisition Typology ......................................................... 96 6.1 Descriptive Statistics of Ratio of Trials to Compounds ........................... 105 6.2 t test on Ratios of Trials to Compounds in Successive Phases .............. 105 6.3 Summary of Association of Acquisition History with Technical Efficiency ..................................................................................................... 112 6.4 Summary of Association of Acquisition History with Financial Efficiency ..................................................................................................... 112 7.1 Results of Tests on Hypothesis H1a ......................................................
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